Machine Learning Research Jobs in Cambridge, MA

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Description

We are looking for a talented and experienced applied ML researcher who can both research new capabilities and develop frontier models using cutting-edge methods. In this role, you will take on high-risk, high-reward challenges - researching, designing, and improving state-of-the-art deep learning models trained on unique data, implementing novel machine learning algorithms, and developing solutions to problems that don't have obvious answers. Your scope will encompass various ML subfields and modalities, combining ideas from different fields to solve unique challenges and deliver solutions adopted broadly across teams.

Responsibilities

• Research and develop cutting-edge deep learning models and algorithms, leveraging multiple data modalities (e.g., vision, audio, sensor, text).

• Design and implement novel neural network architectures solving unique challenges in the field of ASR.

• Navigate ambiguous problem spaces - formulate hypotheses, run experiments, learn from negative results, and iterate toward solutions.

• Improve model performance while maintaining awareness of deployment constraints such as latency, memory, and compute.

• Collaborate across teams, synthesizing approaches from different fields into solutions that work with and benefit the entire organization.

• Communicate findings clearly to stakeholders and team members.

• Stay current with scientific literature on frontier ML methods and identify opportunities to apply new ideas.

Minimum Qualifications

BS in Computer Science, Electrical Engineering, or a related field - or equivalent practical experience.

Experience in academic or industry research.

Experience working with Pytorch.

Preferred Qualifications

MS or PhD in Computer Science, Electrical Engineering, or a related field.

Strong foundation in deep learning theory and hands-on experience training large-scale models.

Deep knowledge in one or more of: self-supervised learning, synthetic data generation, large language model training, or automatic speech recognition.

Experience working with multimodal data (e.g., images, audio, time-series, or sensor fusion).

Strong analytical and problem-solving skills; ability to translate research ideas into production-quality code.

Resilience and persistence - comfort with experimentation cycles where many attempts fail before one succeeds.

Publication record at top-tier ML venues (NeurIPS, ICML, ICLR, Interspeech, ICASSP, etc.).

Multidisciplinary background spanning fields such as neuroscience, physics, signal processing, or mathematics. Experience collaborating with distributed teams across time zones.

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $132,100 and $199,000, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.